Qualification Type: | PhD |
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Location: | Bristol |
Funding for: | UK Students, EU Students |
Funding amount: | From £18,662 per annum in 2023/24 |
Hours: | Full Time |
Placed On: | 3rd March 2022 |
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Closes: | 30th November 2023 |
Funding amount: £18,662 per annum in 2023/24 subject to eligibility status and confirmation of award
The project:
Video technology is now pervasive, with mobile video, UHDTV, video conferencing, and surveillance all underpinned by efficient signal representations. As one of the most important research topics in video processing, compression is crucial in encoding high quality videos for transmission over band-limited channels.
The last three decades have seen impressive performance improvement in standardised video algorithms. The latest standard, VVC and the new royalty free codec, AOM/AV1, are expected to achieve 30-50% gains in coding performance over HEVC. However, this figure is far from satisfactory considering the large amount video data consumed every day.
Inspired by the recent breakthrough in artificial intelligence, in particular deep learning techniques developed for video processing applications, this PhD project will investigate novel deep learning-based video coding tools, network architectures and perceptual loss functions specifically for the new emerging open-source codec, AOM/AV2.
This project is jointly funded by Netflix (US) and MyWorld UKRI Strength in Places Programme, as part of the strategic research collaboration project between the University of Bristol and Netflix (US). The student will have the opportunity to work with experts from Netflix, contributing to the development of AOM/AV2.
URL for further information: http://www.myworld-creates.com/
https://www.bristol.ac.uk/news/2020/june/myworld-ukri-funding-announcement.html
How to apply:
Please visit https://www.bristol.ac.uk/study/postgraduate/2022/eng/phd-elec-electronic-eng/ for candidate requirements
Basic skills and knowledge required include excellent analytical skills and experimental acumen. And a background understanding in one or more of the following: Video Compression; Artificial intelligence/Machine learning/Deep learning
Contacts:
For questions about eligibility and the application process please contact sceem-pgr-admissions@bristol.ac.uk
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